Análisis temporal
df <- read.csv("./BDD_DICIEMBRE_2022.csv")
df$FECHA <- dmy(df$FECHA)
fechas <- data.frame(table(df$FECHA))
colnames(fechas) <- c("Fecha","Freq")
fechas$Fecha <- ymd(fechas$Fecha)
head(fechas)
#class(fechas$Fecha)
library(highcharter)
highchart(type = "stock") %>%
hc_add_series(
data = fechas,
type = "line",
hcaes(x=Fecha,
y=Freq,
group=year(Fecha)))
df %>%
hchart(
type = column,)
sin_mes_fer <- data.frame(table(df$MES_1, df$FERIADO))
colnames(sin_mes_fer) <- c("Mes", "Feriado", "Freq")
hchart(sin_mes_fer,
type = "column",
hcaes(x=Mes,y=Freq,group=Feriado),
stacking = "normal")
df$MES_1 <- factor(df$MES_1, levels= c("ENERO", "FEBRERO", "MARZO",
"ABRIL", "MAYO", "JUNIO", "JULIO",
"AGOSTO","SEPTIEMBRE","OCTUBRE",
"NOVIEMBRE","DICIEMBRE"))
mes <- ggplot(data = df, aes(x=MES_1, fill=FERIADO))+
geom_bar(
position = "stack",
width = 0.7
)+
theme(
axis.text.x = element_text(angle = 45)
)
font = list(
family = "DM S",
size = 15,
color = "white"
)
label = list(
bgcolor = "#232F34",
bordercolor = "transparent",
font = font
)
ggplotly(mes, tooltip=c("y")) %>%
style(hoverlabel = label) %>%
layout(font = font)
unique(df$ANIO)
[1] 2017 2018 2019 2020 2021 2022
gmes <- ggplot(data = df, aes(x=ANIO, fill=FERIADO))+
geom_bar(
position = "stack",
width = 0.7
)
gauto <- data.frame(table(df$TIPO_DE_VEHICULO_1, df$ANIO))
colnames(gauto) <- c("Auto", "Año", "Freq")
#df %>%
ggauto <- ggplot(data = gauto, aes(x=Año, y=Freq, group=Auto, colour=Auto))+
geom_line()
ggplotly(ggauto)
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